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动态复杂性状遗传结构研究的统计模型(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2006年03期
Page:
1-12
Column:
研究论文
publishdate:
2006-03-20

Article Info:/Info

Title:
Statistical Models for Studying the Genetic Architecture of Dynamic Complex Traits
Article ID:
1000-2006(2006)03-0001-12
Author(s):
WU Rong-ling12 LIN Min1 ZHAO Wei1 HOU Wei1 ZHANG Bo2 ZHUGE Qiang2 HUANG Min-ren2 XU Li-an2
1. Department of Statistics University of Florida, Gainesville, FL 32611, USA; 2. The Key Laboratory of Forest Genetics and Gene Engineering of the State Forestry Administration and Jiangsu Province Nanjing Forestry University, Nanjing 210037, China
Keywords:
Developmental trajectory Dynamic trait Statistical model Functional mapping Quantitative trait loci Quantitative trait nucleotides
Classification number :
S722
DOI:
10.3969/j.jssn.1000-2006.2006.03.001
Document Code:
A
Abstract:
Many quantitative traits of agricultural, biological and biomedical importance alter their phenotypes over development and display a complicated dynamic feature. Traditional approaches for genetic mapping of these so called dynamic traits have been to associate markers with phenotypes for different ages or stages of development and to compare the differences across these stages, or to use multiple trait mapping where the same character is repeatedly measured at different times. In either case, these approaches does not capture the dynamic structure and pattern of the process, which greatly limits the scope of inference about its genetic architecture. To overcome these limitations, Functional Mapping, that is, the integration of the mathematical aspects of the biological mechanisms and processes of the traits within the statistical genetic mapping framework, is the natural way to approach the genetics of dynamic traits. The combination of statistical modelling, genetics, and developmental biology begs many questions, such as the patterns of genetic control over development, the duration of QTL effects, as well as what causes developmental trajectories to change or stop changing. This paper shows that the functional mapping provides a useful quantitative and testable framework for assessing the interplay between gene actions/interactions and developmental patterns.

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Last Update: 2013-05-20